Materials in the real world exhibit spatial variations that arise naturally over the course of time. Large scale variations in material appearance are mainly influenced by global factors such as object geometry and weathering environment, while the local variations in weathered appearance are often intrinsic to the material, a natural characteristic of how it looks.
One approach for generating time-variant material appearance is to visually simulate the distribution of weathering effects on a 3-Dimensional (3D) model. Existing visual simulation techniques can successfully generate large scale variations of material appearance based on global factors such as object geometry and weathering environment. However, these techniques are limited in their ability to produce local characteristics that are intrinsic to a material.
An alternative approach is to simulate the weathering interactions of a material based on physical principles. While realistic results have been produced through such simulations, they require substantial computation, and for each new material a complete understanding of its physical weathering process needs to be developed. Another way to obtain physically accurate appearance is to capture a video of a material over time to obtain real-life information on how appearance changes as weathering progresses. Such data-intensive techniques are often challenging in practice because of the need for considerable labor and time. Moreover, technical difficulties with image registration and data storage arise when recording time-variant Bidirectional Reflectance Distribution Functions (BRDFs) in addition to surface colors.